<i>mexEF-oprN</i> Multidrug Efflux Operon of <i>Pseudomonas aeruginosa</i> : Regulation by the MexT Activator in Response to Nitrosative Stress and Chloramphenicol
Bibliographic record
Abstract
A null mutation in the mexS gene of Pseudomonas aeruginosa yielded an increased level of expression of a 3-gene operon containing a gene, xenB, whose product is highly homologous to a xenobiotic reductase in Pseudomonas fluorescens shown previously to remove nitro groups from trinitrotoluene and nitroglycerin (D. S. Blehert, B. G. Fox, and G. H. Chambliss, J. Bacteriol. 181:6254, 1999). This expression, which paralleled an increase in mexEF-oprN expression in the same mutant, was, like mexEF-oprN, dependent on the MexT LysR family positive regulator previously implicated in mexEF-oprN expression. As nitration is a well-known result of nitrosative stress, a role for xenB (and the coregulated mexEF-oprN) in a nitrosative stress response was hypothesized and tested. Using s-nitrosoglutathione (GSNO) as a source of nitrosative stress, the expression of xenB and mexEF-oprN was shown to be GSNO inducible, although in the case of xenB, this was seen only for a mutant lacking MexEF-OprN. In both instances, this GSNO-inducible expression was dependent upon MexT. Chloramphenicol, a nitroaromatic antimicrobial that is a substrate for MexEF-OprN, was shown to induce mexEF-oprN but not xenB, again dependent upon the MexT regulator, possibly because it resembles a nitrosated nitrosative stress product accommodated by MexEF-OprN.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".